1. Field of the Invention
The invention relates to a method with a system for ascertaining and predicting a motion of at least one target object by using a mathematical method of estimation with the aid of a filter method relating to the model assumption for estimating the motion and/or orientation of the target object. The invention also relate to a system for performing the method.
2. Discussion of Background Information
So-called tracking systems, which are able to register a motion of an object by a model assumption, are known. These systems utilize so-called filter equations. A tracking system serves for guiding an interceptor missile that is intended to hit a target object, for example a ballistic target missile. A target object—for example, a ballistic target missile—is distinguished in that it does not have a propulsion unit of its own. Such a missile is designated in German technical language as an unmanned, autonomous flying vehicle, so that ordinary aircraft are not covered by this concept.
The filter equations permit filter methods that, in principle, are mathematical methods of estimation. Known filter methods accordingly use model assumptions for estimating the state of the target missile.
A filter solution that has been preferred up until the present time is based on a so-called Kalman filter or extended Kalman filter.
In the event of abrupt changes of state or abrupt changes in the flight motion of the target missiles, these methods have a poor performance as a rule.
Filters of this type are described in, for example, the publication by G. Minkler, J. Minkler: Theory and Application of Kalman Filtering, Magellan Book Company, Palm Bay, 1993.
Other known filters, such as the so-called particle filter or the unscented filter, also do not solve this problem.
Unscented filters are known from, for example, the publication by B. Ristic, S. Arulampalam, N. Gordon: Beyond the Kalman Filter, Artech House Publishers, Boston, 2004.
Because these filter methods do not permit, or only inadequately permit, the modeling of abrupt changes of state or changes of maneuver, the filters react sluggishly or defectively in the event of such maneuvers.
This is because the underlying model assumptions concerning the motion of the object cannot, for mathematical reasons, map random, discontinuous changes in the characteristics of the target objects, such as accelerations for example. In practice, non-linearities arise in addition, so that an estimation based on these methods is inaccurate.
In order to lessen this problem, it is known to provide an upstream application of integrity algorithms. In this case, use is made of a filter bank with several filters. If deviations of the predicted data, based on the model assumptions, from the measured data are too great, the measurements are discarded, or switching takes place to a different filter of the filter bank. By this means, although the problem can be alleviated in practice, the sluggishness still persists by reason of the behavior of the target object, which is difficult to model.
An interception of highly maneuverable targets such as ballistic missiles, in particular by an interceptor missile, is likewise rendered distinctly difficult in these cases, resulting in a low hit-rate of the interceptor missile.